Digital Health (Jun 2024)

Assessing usability of intelligent guidance chatbots in Chinese hospitals: Cross-sectional study

  • Yanni Yang,
  • Siyang Liu,
  • Ping Lei,
  • Zhengwei Huang,
  • Lu Liu,
  • Yiting Tan

DOI
https://doi.org/10.1177/20552076241260504
Journal volume & issue
Vol. 10

Abstract

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Objective This study aimed to assessing usability of intelligent guidance chatbots (IGCs) in Chinese hospitals. Methods A cross-sectional study based on expert survey was conducted between August to December 2023. The survey assessed the usability of chatbots in 590 Chinese hospitals. One-way ANOVA was used to analyze the impact of the number of functions, human-like characteristics, number of outpatients, and staff size on the usability of the IGCs. Results The results indicate that there are 273 (46.27%) hospitals scoring above 45 points. In terms of function development, 581(98.47%) hospitals have set the number of functions between 1 and 5. Besides, 350 hospitals have excellent function implementation, accounting for 59.32%. In terms of the IGC's human-like characteristic, 220 hospitals have both an avatar and a nickname. Results of One-way ANOVA show that, the number of functions( F = 202.667, P < 0.001), human-like characteristics( F = 372.29, P < 0.001), staff size( F = 9.846, P < 0.001), and the number of outpatients( F = 5.709, P = 0.004) have significant impact on the usability of hospital IGCs. Conclusions This study found that the differences in the usability of hospital IGCs at various levels of the number of functions, human-like characteristics, number of outpatients, and staff size. These findings provide insights for deploying hospital IGCs and can inform improvements in patient's experience and adoption of chatbots.